| dc.contributor.author |
TAMBOURATZIS, G |
en |
| dc.contributor.author |
TAMBOURATZIS, D |
en |
| dc.date.accessioned |
2014-06-06T06:42:36Z |
|
| dc.date.available |
2014-06-06T06:42:36Z |
|
| dc.date.issued |
1994 |
en |
| dc.identifier.issn |
0954-898X |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/709 |
|
| dc.subject.classification |
Computer Science, Artificial Intelligence |
en |
| dc.subject.classification |
Engineering, Electrical & Electronic |
en |
| dc.subject.classification |
Neurosciences |
en |
| dc.title |
SELF-ORGANIZATION IN COMPLEX PATTERN SPACES USING A LOGIC NEURAL-NETWORK |
en |
| heal.type |
journalArticle |
en |
| heal.language |
English |
en |
| heal.publicationDate |
1994 |
en |
| heal.abstract |
This article investigates the behaviour of a self-organizing logic neural network when it is tasked with clustering complex data spaces. The network is based on the discriminator-node structure and is trained using an unsupervised-learning adaptation rule. The network performance is evaluated by applying it to clustering tasks involving identifiable classes, each of which consists of a large number of distinct subclasses. The results presented are supported by a statistical analysis, which indicates that the system is indeed suited to clustering such complex data sets. |
en |
| heal.publisher |
IOP PUBLISHING LTD |
en |
| heal.journalName |
NETWORK-COMPUTATION IN NEURAL SYSTEMS |
en |
| dc.identifier.issue |
4 |
en |
| dc.identifier.volume |
5 |
en |
| dc.identifier.isi |
ISI:A1994PV48800010 |
en |
| dc.identifier.spage |
599 |
en |
| dc.identifier.epage |
617 |
en |